PROJECT SUMMARY Whether it's choosing between dinner locations, health plans or investment vehicles for our savings, many decisions involve a tradeoff between exploring options that are unknown and exploiting options we know well. Making such explore-exploit decisions ?correctly?, i.e. in such a way as to maximize long-term gain, is surprisingly difficult and mathematically optimal solutions are intractable in most cases. Despite this difficulty, we have recently shown that young people make remarkably effective explore-exploit decisions using a mixture of two strategies: directed exploration, in which information seeking drives exploration by choice, and random exploration, in which adaptive behavioral variability drives exploration by chance. Despite this progress, little is known about how directed and random exploration are implemented in the brain, and almost nothing is known about how these strategies change in old age. Given the ubiquity of these decisions in daily life, we believe this is a critical omission if we are to understand decision making in aging and cognitive decline. The objective of this proposal is to develop and test a neurocomputational model that describes explore-exploit decision making. In this model, we propose that the overall balance between exploration and exploitation is set by activity in a specific set of brain areas. Our central hypothesis is that age-related changes in explore-exploit behavior can be accounted for by age-related changes in this circuit. To test this hypothesis we will pursue three Specific Aims that test key predictions of this neurocomputational model as it applies to healthy aging. Aim 1 will test the behavioral predictions of this model by characterizing the explore-exploit behavior of a large sample of healthy younger and healthy older adults. Aim 2 will map the brain areas involved in directed and random exploration using functional and structural magnetic resonance imaging. Finally, in Aim 3 we will manipulate directed and random exploration using transcranial magnetic stimulation (TMS) to perturb neural firing in key areas of the explore-exploit network. The proposed research is innovative as the first to study directed and random exploration in older adults, the first to probe the neural correlates of these strategies, and the first to manipulate explore-exploit behavior in older adults with TMS. In addition, by testing the predictions of the circuit model, this work will build towards a neurocomputational account of explore-exploit behavior. This model will have significant impact on our understanding of decision making in old age and provide a framework for understanding how these decisions change with cognitive decline and Alzheimer's disease. Finally, if our TMS manipulations are successful, we will open the possibility of using neural stimulation to enhance explore-exploit decision making in cases where it is impaired.